ObjectiveThis study aims to explore the potential of different orders of magnitude single-nucleotide polymorphism (SNP) locus combinations for predicting distant kinship relationships. A high-density SNP locus set was constructed, and a comprehensive assessment of its inference capability was conducted. MethodsFirstly, we selected three commercial chip panels, CGA (Chinese genotyping array, Illumina), GSA (Global screening array, Illumina), Affy (23MF_V2 high-density SNP array, Affymetrix) and merged them after quality control, forming a high-density SNP locus panel(1 180 k). Secondly, we selected 161 samples and collected their peripheral blood samples by using whole-genome sequencing technology. Within this sample population, the levels of kinship relationships fully covered the range from level 1 to level 9, and the number of kinship pairs at each level was consistently maintained at over 50 pairs. From 161 samples data of whole-genome sequencing, the 1 180 k locus set was extracted, which is referred to as the high-density SNP locus set in the following text. The kinship inference was conducted using the identity-by-descent (IBD) algorithm with the selected optimal parameters. To comprehensively evaluate the performance of the high-density SNP locus set in kinship inference, we compared it with the three commercial chip panels, the intersection of these three chip loci, and the control sets constructed by randomly reducing the number of the high-density SNP locus set. Based on the changes in the IBD lengths, as well as the dynamic trends in prediction accuracy, we conducted a scientific assessment of the kinship inference capability of the high-density SNP locus set. ResultsAfter screening, a set of 1 184 334 autosomal SNPs was obtained. During the process of screening the optimal IBD length threshold, the result revealed that 0 cM, 1 cM, and 2 cM all demonstrated good applicability. However, to avoid the issue of a large amount of redundant information caused by setting a too low IBD length threshold, this study ultimately selected 2 cM as the optimal threshold. Compared with the average results of three chip panels, the high-density SNP locus set increased the total IBD length and the average IBD length across levels 1-9; the accuracy of the confidence interval for level 8 was 70.97%, which represented a 3.50% improvement; the average confidence interval accuracy for levels 1-8 was 91.39%, representing a 1.00% increase; and the false negative rates at levels 8 and 9 were reduced by 2.42% and 6.76%, respectively. The system efficacy of the high-density SNP locus set for kinship inference of first to eighth degree relationships reached 98.91%. Through random reduction of the high-density SNP locus set results, it is found that increasing the number of SNPs with the panel, the detection efficiency of IBD length showed a significant upward trend. At the same time, the overall trend in the accuracy of kinship relationship prediction as well as the confidence interval accuracy also indicated that both metrics steadily increased with the addition of more loci. ConclusionThe results show that the high-density SNPs panel significantly enhances the efficacy of distant kinship inference, accurately covering kinship degrees, with the average confidence interval accuracy for first to eighth degree relationships stably above 90%. The study finds that increasing the number of SNPs panel can improve the ability to predict distant kinship.

Parkinson’s disease (PD) is a common neurodegenerative disorder with profound impact on patients’ quality of life and long-term health, and early detection and intervention are particularly critical. In recent years, the search for precise and reliable biomarkers has become one of the key strategies to effectively address the clinical challenges of PD. In this paper, we systematically evaluated potential biomarkers, including proteins, metabolites, epigenetic markers, and exosomes, in the peripheral blood of PD patients. Protein markers are one of the main directions of biomarker research in PD. In particular, α‑synuclein and its phosphorylated form play a key role in the pathological process of PD. It has been shown that aggregation of α-synuclein may be associated with pathologic protein deposition in PD and may be a potential marker for early diagnosis of PD. In terms of metabolites, uric acid, as a metabolite, plays an important role in oxidative stress and neuroprotection in PD. It has been found that changes in uric acid levels may be associated with the onset and progression of PD, showing its potential as an early diagnostic marker. Epigenetic markers, such as DNA methylation modifications and miRNAs, have also attracted much attention in Parkinson’s disease research. Changes in these markers may affect the expression of PD-related genes and have an important impact on the onset and progression of the disease, providing new research perspectives for the early diagnosis of PD. In addition, exosomes, as a potential biomarker carrier for PD, are able to carry a variety of biomolecules involved in intercellular communication and pathological regulation. Studies have shown that exosomes may play an important role in the pathogenesis of PD, and their detection in blood may provide a new breakthrough for early diagnosis. It has been shown that exosomes may play an important role in the pathogenesis of PD, and their detection in blood may provide new breakthroughs in early diagnosis. In summary, through in-depth evaluation of biomarkers in the peripheral blood of PD patients, this paper demonstrates the important potential of these markers in the early diagnosis of PD and in the study of pathological mechanisms. Future studies will continue to explore the clinical application value of these biomarkers to promote the early detection of PD and individualized treatment strategies.

Objective To investigate the effect of simple carbohydrate given 2 h before operation on postoperative insulin resistance and gastrointestinal function in elderly patients with trauma undergoing spinal anesthesia.Methods This was a randomized controlled clinical study.A total of 90 elderly patients with intertrochanteric femoral fracture/femoral neck fracture admitted to the Traumatic Orthopedics Department of the Fourth Medical Center of Chinese PLA General Hospital from October 2023 to February 2024 were randomly divided equally into control group(fasting with water before surgery)and carbohydrate group(CHO group,drinking 200 ml of pulsatile water at 2 h before surgery).All the patients received spinal anesthesia.The control group excluded 2 patients who completed surgery and were admitted to the ICU,2 patients received epidural anesthesia,and finally included 41 patients;3 patients were excluded from the CHO group under epidural anesthesia,2 patients underwent surgery under general anesthesia,and finally 40 patients were included.Baseline data of patients were collected,including gender,age,Charlson comorbidity index(CCI),presence or absence of diabetes,body mass index(BMI),American Association of Anesthesiologists(ASA)classification,etc.The patient's surgical time,intraoperative blood loss,first postoperative exhaust time,type of surgery,length of hospital stay,mean arterial pressure(MAP)and heart rate(HR)at four time points during surgery[entry(T1),post-anesthesia(T2),mid-operation(T3),and exit(T4)],perioperative blood glucose,insulin levels,C-reactive protein(CRP),and intestinal barrier function indicators(diamine oxidase,D-lactate,and bacterial endotoxin),as well as self-rating anxiety scale(SAS),visual analogue scale of pain(VAS),and Ramsay scores were recorded.Preoperative and postoperative use of the delirium diagnostic scale(3D-CAM)assessed the presence of delirium in patients.Results Eighty-one patients aged(77.7±9.5)years were included.Compared with control group,the first exhaust time in CHO group was significantly shorter[4.59(3.25,7.39)h vs.10.23(7.97,14.76)h,P<0.001],postoperative insulin resistance index(HOMA-IR)was significantly decreased[5.13(2.38,10.30)vs.7.34(2.31,12.55),P<0.001].The change rate of HOMA-IR(ΔHOMA-IR)also decreased significantly(P<0.001);There were no significant differences in intestinal barrier function indexes between the two groups(P>0.05);The levels of D-lactic acid and bacterial endotoxin in control group were significantly increased after operation,and the differences were statistically significant(P=0.010,P=0.031),In CHO group,there was no significant difference in preoperative and postoperative indexes(P>0.05).There was no significant difference in the perioperative scale score,incidence of delirium and the length of hospital stay between the two groups(P>0.05).Conclusions Taking simple carbohydrates 2 h before surgery can significantly shorten the first exhaust time,reduce insulin resistance and the incidence of delirium,and improve gastrointestinal function in elderly trauma patients undergoing spinal anesthesia,thus providing clinical basis for accelerated postoperative rehabilitation in elderly patients.

Objective In this preliminary survey,we sought to determine the composition of mosquito species inhabiting the Emeifeng Nature Reserve,Fujian Province,China.Methods Mosquito larvae were collected by straw and spoon trapping,and adult mosquitoes were collected by lamp trapping at selected breeding sites in the reserve.The specimens were initially identified based on morphology,with subsequent verification using molecular biology methods.Results A total of 34 mosquito species in 13 genera were collected,among which,there were 4 species of Anopheles(Genus Anopheles Meigen,1818),2 species of Lutzia(Genus Lutzia Theobald,1903),15 species of Culex(Genus Culex Linnaeus,1758),4 species of Stegomyia(Genus Stegomyia Theobald,1901),and single species of Hulecoeteomyia(Genus Hulecoeteomyia Theobald,1904),Luius(Genus Luius Reinert,Harbach et Kitching,2008),Aedes(Genus Aedes Meigen,1818),Downsiomyia(Genus Downsiomyia Vargas,1950),Collessius(Genus Collessius Reinert,Harbach et kitching,2006),Uranotaenia(Genus Uranotaenia Lynch 1891),Armigeres(Genus Armigeres Theobald,1901),Toxorhynchites(Genus Toxorhynchites Theobald,1901),and pestle mosquito(Genus Tripteroides Giles,1904).Conclusions The species composition of mosquitoes sampled in the Emeifeng Nature Reserve will provide a basis for further research on mosquito vectors and contribute to measures for local mosquito control.

Aim To explore the effect of astragalosideⅣ(AS-Ⅳ)on lipopolysaccharide(LPS)-induced po-larization and migration of RAW 264.7 macrophages and the underlying mechanism.Methods 1 mg·L-1 LPS was used to construct cell migration model.Scratch assay was utilized to determine cell migration rate.Immunofluorescence staining was utilized to de-tect the expression and location of F4/80,iNOS and Arg-1.CCK-8 assay was used to determine the viabili-ty of RAW 264.7 cells.Griess assay was used to measure NO content.Molecular docking was used to analyze the interaction between AS-Ⅳ and the core tar-gets such as cGAS and STING protein.Western blot was employed to detect the expression of iNOS,Arg-1,cGAS,STING,NF-κB p65 and p-NF-κB p65 protein.Results AS-Ⅳ significantly inhibited the migration and M1 polarization of RAW 264.7 cells induced by LPS.Moreover,AS-Ⅳ could interact with cGAS and STING protein,especially cGAS.Further Western blot assay showed that AS-Ⅳ significantly downregulated the expression of iNOS,cGAS,STING and p-NF-κB p65 protein.Conclusions AS-Ⅳ could promote mac-rophage M1 to M2 polarization,thereby inhibited mac-rophage migration through restraining the cGAS/STING/NF-κB signaling pathway,which provides a new therapeutic target for AS-Ⅳ to improve the early inflammatory response of AS.

Objective To establish a method for determining the concentration of contezolid in human cerebro spinal fluid(CSF)using ultra high performance liquid chromatography tandem mass spectrometry(UPLC-MS/MS).Methods Linezolid as the internal standard(IS)and acetonitrile as the protein precipitant.Waters ACQUITY UPLC? BEH C18(2.1 mm × 50.0 mm,1.7 μm)chromatographic column was used for separation,with a mobile phase of 0.1％formic acid aqueous solution-0.1％formic acid acetonitrile solution,gradient elution method,flow rate was 0.4 mL·min-1,column temperature was 40 ℃,automatic sampler temperature was 10 ℃,the analysis time was 4 minutes.Electrospray ion source,positive ion mode,and multi-reaction monitoring scanning mode were used.The monitoring and analysis ion pairs for contezolid were m/z 409.15→269.14,and the monitoring ion pairs for linezolid were m/z 338.14 → 195.10.The specificity,standard curve and lower limit of quantification(LLOQ),precision and recovery rate,matrix effect,residual effect,dilution effect and stability of the method were investigated.Results The endogenous substances in CSF do not interfere with the determination of the analyte contezolid and the internal standard linezolid,and the method has good specificity.Satisfactory linearity was observed within the concentration range of 20-5 000 ng·mL-1 for contezolid in CSF,the calibration curve was y=8.97 × 10-4x+1.95 × 10-2(r=0.999 1),and the LLOQ was 20 ng·mL-1.Precision of the intra-batch and inter-batch relative standard deviation(RSD)＜15％,and the extraction recovery were 90.96％-98.71％.The average normalized matrix effect factor of the quality control CSF sample were 94.39％-100.25％.The RSD of dilution effect＜15％.The CSF samples of contezolid were stored at room temperature,in the automatic sampler for 72 hours,-20 ℃ and-80 ℃ for 90 days,and subjected to repeated freezing and thawing three times,were stable with all of which the RSD＜10％.Conclusion This method is high sensitivity,rapid,simple and accurate,which is very suitable for the therapeutic drug monitoring of contezolid in human CSF.

Objective To propose a brain electrical phase prediction method based on long short-term memory network(LSTM)to improve the accuracy and robustness of phase synchronization prediction in transcranial magnetic stimulation(TMS).Methods First,an LSTM consisting of an input layer,an LSTM layer,an ReLU activation layer,a fully connected layer and a regression layer was constructed to capture the EEG signal features through the synergistic action of input gates,forgetting gates and output gates.Second,eye-open resting-state EEG data from 30 healthy subjects were trained using the LSTM to obtain a predictive model for EEG signal and EEG phase prediction.Finally,the LSTM method and the traditional autoregressive(AR)method were compared in terms of the phase prediction errors at the overall and individual levels and the prediction performance for peaks and troughs.A regression model was used to explore the relationships between instantaneous EEG amplitude,signal-to-noise ratio and phase prediction error with the LSTM method.Results The LSTM method achieved a total phase prediction error of 0.04°±5.69°,which was lower than that of the traditional AR method(-3.36°±51.13°).For each subject,the LSTM method demonstrated superior phase prediction accuracy compared to the traditional AR method(P＜0.001).The accuracy for predicting peaks(troughs)by the LSTM method(about 89％)was higher than that by the traditional AR method(about 10％).Unlike the traditional AR method,the LSTM method didnot result in linear relationships between instantaneous EEG amplitude,signal-to-noise ratio and phase prediction error,with Pvalues being 0.58 and 0.18,respectively.Conclusion The LSTM-based brain electrical phase prediction method shows high accuracy and robustness when used for EEG phase-synchronized TMS.[Chinese Medical Equipment Journal,2025,46(3):1-8]

Depression is a heterogeneous mental disorder in which the interaction between genetic susceptibility and environ-mental factors plays a key role in its pathogenesis.Although the specific mechanisms of the disease still need to be thoroughly studied and elucidated,there is now a broad consensus that epi-genetic markers have a central influence on its mechanism of ac-tion.DNA methylation of brain-derived neurotrophic factor(BD-NF)is not only regarded as a promising epigenetic biomarker of pathology,but may also help predict the efficacy of antidepres-sants.In this paper we reviewed the gene structure of BDNF and its DNA methylation regulation mechanism,and also analyzed the changes of DNA methylation of this factor in depression pa-tients and animal models,aiming to provide new ideas and theo-retical support for clinical research.

Background:Postoperative nutritional status and nutritional support therapy are important driving factor for clinical outcomes in patients after lung transplantation.This study aims to evaluate the relationship between mNUTRIC scores and prognosis in patients after lung transplantation.Methods:A retrospective inclusion of 253 patients who underwent lung transplantation at Wuxi People's Hospital Affiliated to Nanjing Medical University from January 2020 to December 2022.The nutritional risk in patients after lung transplantation is much higher than in other critically ill patients.To explore the optimal threshold,patients were divided into three groups based on the tertiles of mNUTRIC scores,and clinical outcomes were compared.The predictive ability of the mNUTRIC score was analyzed using receiver operating characteristic(ROC)curve.The appropriate threshold was determined using the Youden index based on the highest combined sensitivity and specificity.Results:Among 253 patients,the 30-day mortality rate was 14.2%.The death group had higher age and BMI,with APACHE II,SOFA,and mNUTRIC scores all higher than those in the survival group.The median mNUTRIC score in the death group was 5.00(3.00～6.00).The higher the mNUTRIC score,the greater the gradual increase in 30-day mortality rate.When the mNUTRIC score was 4～6,the patient mortality rate was 21.21%,and when 7～9,it was 42.31%.The Q3 group had significantly prolonged mechanical ventilation time,was more prone to delayed weaning,had longer ICU length of stay,and higher tracheotomy rate.Multivariate Cox regression analysis and Kaplan-Meier survival curve showed that mNUTRIC score is an independent risk factor for 30-day mortality,with mortality rate increasing as the score increased(P<0.001).The area under the ROC curve(AUC)for mNUTRIC score was 0.765(95%CI:0.686,0.644).According to the Youden index,the optimal cutoff value is when mNUTRIC score equals 3.5,used to predict high nutritional risk and 30-day mortality in lung transplant patients.Conclusion:The mNUTRIC score has a good predictive effect on the prognosis of patients after lung transplantation and is expected to be applied in clinical practice as a routine assessment tool to help clinicians perform postoperative nutritional risk stratification.

Objective To propose a brain electrical phase prediction method based on long short-term memory network(LSTM)to improve the accuracy and robustness of phase synchronization prediction in transcranial magnetic stimulation(TMS).Methods First,an LSTM consisting of an input layer,an LSTM layer,an ReLU activation layer,a fully connected layer and a regression layer was constructed to capture the EEG signal features through the synergistic action of input gates,forgetting gates and output gates.Second,eye-open resting-state EEG data from 30 healthy subjects were trained using the LSTM to obtain a predictive model for EEG signal and EEG phase prediction.Finally,the LSTM method and the traditional autoregressive(AR)method were compared in terms of the phase prediction errors at the overall and individual levels and the prediction performance for peaks and troughs.A regression model was used to explore the relationships between instantaneous EEG amplitude,signal-to-noise ratio and phase prediction error with the LSTM method.Results The LSTM method achieved a total phase prediction error of 0.04°±5.69°,which was lower than that of the traditional AR method(-3.36°±51.13°).For each subject,the LSTM method demonstrated superior phase prediction accuracy compared to the traditional AR method(P＜0.001).The accuracy for predicting peaks(troughs)by the LSTM method(about 89％)was higher than that by the traditional AR method(about 10％).Unlike the traditional AR method,the LSTM method didnot result in linear relationships between instantaneous EEG amplitude,signal-to-noise ratio and phase prediction error,with Pvalues being 0.58 and 0.18,respectively.Conclusion The LSTM-based brain electrical phase prediction method shows high accuracy and robustness when used for EEG phase-synchronized TMS.[Chinese Medical Equipment Journal,2025,46(3):1-8]